# -*- coding: utf-8 -*-
from utils.operators.cluster_for_spark_sql_operator import SparkSqlOperator
from datetime import timedelta

from jms.dwd.tab.dwd_tab_barscan_sign_base_dt import jms_dwd__dwd_tab_barscan_sign_base_dt
from jms.dwd.tab.dwd_tab_barscan_collect_base_dt import jms_dwd__dwd_tab_barscan_collect_base_dt
from jms.dwd.oms.dwd_yl_oms_oms_waybill_incre_dt import jms_dwd__dwd_yl_oms_oms_waybill_incre_dt
from jms.dwd.tab.dwd_tab_barscan_unloading_base_dt import jms_dwd__dwd_tab_barscan_unloading_base_dt
from jms.dwd.tab.dwd_tab_barscan_deliver_base_dt import jms_dwd__dwd_tab_barscan_deliver_base_dt
from jms.dim.dim_lmdm_sys_network_manage import jms_dim__dim_lmdm_sys_network_manage
from jms.dwd.tab.dwd_tab_reback_transfer_express_base import jms_dwd__dwd_tab_reback_transfer_express_base
from jms.dim.dim_tab_abnormal_network_config_base_dt import jms_dim__dim_tab_abnormal_network_config_base_dt


jms_dm__dm_waybill_sign_abnormal_detail_dt = SparkSqlOperator(
    task_id='jms_dm__dm_waybill_sign_abnormal_detail_dt',
    task_concurrency=1,
    pool_slots=2,
    master='yarn',
    #execution_timeout=timedelta(hours=2)
    #excel平均时长:11分46秒
    execution_timeout = timedelta(minutes=45),
    email=['suning@jtexpress.com','yl_bigdata@yl-scm.com'],
    name='jms_dm__dm_waybill_sign_abnormal_detail_dt_{{ execution_date | date_add(1) | cst_ds }}',
    sql='jms/dm/dm_waybill_sign_abnormal_detail_dt/execute.hql',
    executor_cores=6,
    executor_memory='20G',
    num_executors=15,  # spark.dynamicAllocation.enabled 为 True 时，num_executors 表示最少 Executor 数
    conf={
        'spark.dynamicAllocation.enabled': 'true',  # 动态资源开启
        'spark.shuffle.service.enabled' : 'true',  # 动态资源 Shuffle 服务开启
        #'spark.dynamicAllocation.maxExecutors'  : 100,  # 动态资源最大扩容 Executor 数
          'spark.dynamicAllocation.maxExecutors'  : 41,  # 动态资源最大扩容 Executor 数
        'spark.dynamicAllocation.cachedExecutorIdleTimeout': 60,  # 动态资源自动释放闲置 Executor 的超时时间(s)
        'spark.sql.sources.partitionOverwriteMode' : 'dynamic',  # 允许删改已存在的分区
        'spark.executor.memoryOverhead'  : '4G',  # 堆外内存
        'spark.sql.shuffle.partitions'  : 2000,
        'spark.default.parallelism'  : 600,
        'spark.sql.auto.repartition' :'true'
    },
    #hiveconf={
    #    'hive.exec.dynamic.partition' : 'true',  # 动态分区
    #    'hive.exec.dynamic.partition.mode' : 'nonstrict',
    #    'hive.exec.max.dynamic.partitions' : 400,  # 每天生成 20 个分区
    #    'hive.exec.max.dynamic.partitions.pernode': 400,  # 每天生成 20 个分区
    #},
)

jms_dm__dm_waybill_sign_abnormal_detail_dt << [
    jms_dwd__dwd_tab_barscan_sign_base_dt,
    jms_dwd__dwd_tab_barscan_collect_base_dt,
    jms_dwd__dwd_yl_oms_oms_waybill_incre_dt,
    jms_dwd__dwd_tab_barscan_unloading_base_dt,
    jms_dwd__dwd_tab_barscan_deliver_base_dt,
    jms_dim__dim_lmdm_sys_network_manage,
    jms_dwd__dwd_tab_reback_transfer_express_base,
    jms_dim__dim_tab_abnormal_network_config_base_dt
]


